Lead Data Architect - AWS (Databricks / Lakehouse)

Role Overview We are seeking a Lead Data Architect to drive the design and evolution of our next-generation data platform on AWS . This is a high-impact leadership role responsible for building scalable, cloud-native data ecosystems and enabling enterprise-wide data-driven decision-making. You will play a critical role in modernizing legacy data platforms , defining Lakehouse architecture , and leading cross-functional teams to deliver robust, high-performance data solutions. Key Responsibilities 🔹 Architecture & Strategy Define and implement enterprise-scale data architecture on AWS Lead modernization initiatives (Data Lake → Lakehouse using Databricks & Delta Lake) Design scalable, secure, and cost-efficient data platforms Establish data governance, quality, and security frameworks 🔹 Engineering Excellence Architect and oversee development of high-performance data pipelines using PySpark & Databricks Optimize Spark workloads, partitioning strategies, and query performance Design real-time and batch processing frameworks 🔹 Leadership & Delivery Lead and mentor data engineers, BI developers, and analysts Drive delivery across multiple data programs and initiatives Collaborate with business stakeholders to translate data needs into scalable solutions Own end-to-end data platform reliability and performance 🔹 Innovation & CoE Build and scale a Data & Analytics Center of Excellence (CoE) Drive adoption of best practices, reusable frameworks, and standards Evaluate and implement emerging technologies in the AWS data ecosystem Must-Have Skills & Experience 10+ years in Data Engineering / Big Data / Data Platforms 3–5+ years of deep hands-on experience with Databricks on AWS Strong expertise in: Apache Spark (internals, optimization, distributed computing) Delta Lake & Lakehouse architecture AWS services (S3, EMR, Glue, Redshift, Lambda, IAM, etc.) Proven experience with large-scale data platforms (Hadoop, Hive, HDFS) Strong proficiency in Python, PySpark, and SQL Experience designing data lakes, data warehouses, and hybrid architectures Expertise in data orchestration tools (Airflow, etc.) Strong understanding of CI/CD, Git, and DevOps for data pipelines Experience with real-time streaming (Kafka, Kinesis) Exposure to multi-cloud environments (Azure / GCP) Knowledge of Data Mesh or Data Fabric concepts Experience in domain-driven data architecture 👥 Leadership Expectations Proven ability to lead cross-functional teams Experience working with enterprise stakeholders and clients Strong communication and decision-making skills Ability to drive data strategy and organizational adoption Employment visa sponsorship Dependent visa support Flight ticket coverage Two weeks of free accommodation Group insurance with inpatient and outpatient allowances